From the African continent comes welcome developments about HIV treatment response. The results of studies across countries show intervention processes could be one possible area for improving treatment response altogether.

New research suggests that pharmacy records can be accurate, and cost-effective, indicators for predicting whether HIV patients in the developing world are at risk of treatment failure.

Failure of first-line antiretroviral drugs (ARVs) is detected in the developed world by measuring the amount of HIV circulating in a patient’s blood. In resource poor settings, however, the WHO recommends that CD4 cell testing — a measure of the health of the immune system — is used.

But CD4 tests indicate treatment failure after it has occurred, while using pharmacy records to measure treatment adherence could indicate patients at risk of treatment failure before it happens, the researchers say.

The researchers calculated adherence by comparing the number of months a patient was prescribed drugs with the number of months the drugs were actually dispensed from pharmacies.

“We assessed the ability of a simple measure — whether the patient collected their monthly medication on time — to predict virological failure,” says clinical pharmacologist Gary Maartens from South Africa’s Groote Schuur Hospital at the University of Cape Town and an author of the research.

They found that monitoring adherence was more accurate than monitoring changes in CD4 levels to determine whether a patient’s treatment had failed in the first year after starting ARVs.

He said the system could work within the public health system with the correct technology and systems. At present, however, only the private health sector has the resources to track adherence, and the researchers say more research needs to be carried out into the effectiveness of adherence monitoring in public health clinics.

Tracking adherence in order to identify and intervene with vulnerable patients should mark a policy switch, the researchers write, “a reason for clinics to organise these data in a way that can be used in simple algorithmic approaches to patient care”.